A multigrid tutorial: second edition
A multigrid tutorial: second edition
Image quilting for texture synthesis and transfer
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Gradient domain high dynamic range compression
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Mosaics of Scenes with Moving Objects
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ACM SIGGRAPH 2003 Papers
What Energy Functions Can Be Minimizedvia Graph Cuts?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Interactive digital photomontage
ACM SIGGRAPH 2004 Papers
ACM SIGGRAPH 2006 Papers
Computer Methods for Creating Photomosaics
IEEE Transactions on Computers
Streaming multigrid for gradient-domain operations on large images
ACM SIGGRAPH 2008 papers
Outdoors augmented reality on mobile phone using loxel-based visual feature organization
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Efficient Extraction of Robust Image Features on Mobile Devices
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Fast image blending using watersheds and graph cuts
Image and Vision Computing
Adaptive planar and rotational image stitching for mobile devices
Proceedings of the 5th ACM Multimedia Systems Conference
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This paper presents a sequential image stitching approach for creating high-quality panoramic images on mobile devices. In this approach, each source image in the image sequence is stitched onto the panoramic image sequentially using two operations: optimal seam finding and transition smoothing. In the seam finding process, graph cut optimization finds an optimal seam and creates labeling in the overlapping area between the current panoramic image and the current source image. The current panoramic image can be updated by merging the current source image using the labeling information. If there are visible stitching artifacts in the seam, a transition smoothing operation is performed to hide the seam and remove the stitching artifacts. In the transition smoothing process, a gradient vector field is created from the gradients of corresponding pixels in the current labeled source image to construct a Poisson equation. A composite image can be recovered from the gradient vector field by solving the Poisson equation with boundary conditions. The current panoramic image is updated by merging the composite image. The approach presents several advantages. The use of graph cut optimization guarantees finding optimal seams and avoids blurring and ghosting problems caused by objects moving between capture of input images or by spatial alignment errors. The gradient domain transition smoothing process reduces color differences and further improves image quality. The sequential panorama stitching procedure enables us to produce high resolution panoramic images with limited memory resources. The approach is implemented and it produces high quality panoramic images on mobile devices. It shows good performance for both indoor and outdoor scenes.